Technology-based ("FinTech") lenders increased their market share of U.S. mortgage lending from 2 percent to 8 percent from 2010 to 2016. Using market-wide, loan-level data on U.S. mortgage applications and originations, we show that FinTech lenders process mortgage applications about 20 percent faster than other lenders, even when controlling for detailed loan, borrower, and geographic observables. Faster processing does not come at the cost of higher defaults. FinTech lenders adjust supply more elastically than other lenders in response to exogenous mortgage demand shocks, thereby alleviating capacity constraints associated with traditional mortgage lending. In areas with more FinTech lending, borrowers refinance more, especially when it is in their interest to do so. We find no evidence that FinTech lenders target marginal borrowers. Our results suggest that technological innovation has improved the efficiency of financial intermediation in the U.S. mortgage market.
We explore the impact of supervision on the riskiness, profitability, and growth of U.S. banks. Using data on supervisors' time use, we demonstrate that the top‐ranked banks by size within a supervisory district receive more attention from supervisors, even after controlling for size, complexity, risk, and other characteristics. Using a matched sample approach, we find that these top‐ranked banks that receive more supervisory attention hold less risky loan portfolios, are less volatile, and are less sensitive to industry downturns, but do not have lower growth or profitability. Our results underscore the distinct role of supervision in mitigating banking sector risk.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper investigates the incentives for banks to bias their internally generated risk estimates. We are able to estimate bank biases at the credit level by comparing bank-generated risk estimates within loan syndicates. The biases are positively correlated with measures of regulatory capital, even in the presence of bank fixed effects, consistent with an effort by low-capital banks to improve regulatory ratios. At the portfolio level, the difference in borrower probability of default is as large as 100 basis points, which can improve the typical loan portfolio's Tier 1 capital ratio by as much as 33 percent. Congruent with a regulatory motive, the sensitivity to capital is greater for larger, riskier, and more opaque credits. In addition, we find that low-capital banks' risk estimates have less explanatory power than those of high-capital banks with regard to the prices set on loans, indicating that low-capital banks not only have downward-biased risk estimates but that they also incorporate less information.
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